By utilizing multiple linear regression to analyze the relationship between patients' length of hospital stay and factors such as age, gender, BMI, and blood type, hospitals can identify key predictors of extended stays. This insight is crucial for optimizing staffing, managing bed availability, and tailoring interventions to reduce hospital stays. Ultimately, understanding these correlations can help hospitals provide better$-$targeted care, improve patient outcomes, and ensure that resources are utilized effectively during high$-$demand periods.

Objective: To analyze the impact of various patient factors on the length of hospital stay using multiple linear regression.

Factors to Consider:

Age

Gender

BMI

Blood Type

Number of pre$-$existing conditions

Severity of flu symptoms $($measured on a scale of $1$ to $10)$